1. Field of the Invention
The present invention relates to mobile or cellular communication systems and more particularly to a system and method for pseudorandom noise (PN) code acquisition in Code Division Multiple Access (CDMA) Direct Sequence Spread Spectrum (DSSS) systems, with automatic decision threshold, based on a combination of the Maximum Likelihood (ML) and Serial Search (SS) acquisition approaches.
2. Prior Art
The primary function of psuedonoise (PN) code synchronization in spread spectrum communication systems, such as the Code Division Multiple Access Direct Sequence Spread Spectrum (CDMA-DSSS) system, is to despread the received PN code for demodulation of the received signal. The received signal in essence consists of two digital signals or bit streams that are combined to create a modulated third signal prior to transmission. The first digital signal is an information signal, such as the output of a digitized voice circuit, which may have a bit rate, for example, of 10 kb/s. The second signal is generated by a random-sequence or pseudonoise (PN) generator and constitutes a stream of essentially random bits having a bit rate that is several orders of magnitude greater than that of the digitized voice signal. The combination or modulated third signal that is actually transmitted has the same bit rate as the faster second signal while containing the slower voice signal.
At the receiver, after carrier frequency demodulation, despreading is accomplished by generating a local replica of the PN code with a random-sequence generator in the receiver and then synchronizing the local PN signal to the one that has been superimposed on the incoming received signal at the transmitter. By removing the random sequence from the received signal and integrating it over a symbol period, a despread signal is obtained which ideally exactly represents the original 10 kb/s voice signal.
The process of the signal synchronization is usually accomplished in two steps. The first step, called acquisition, consists of bringing the two codes or spreading signals into coarse time alignment within one code chip interval. The second step, called tracking, takes over and continuously maintains the best possible waveform alignment by means of a feedback loop. The focus of the present invention is on the acquisition aspect of the synchronization system.
Because of the importance of synchronization (or acquisition), many schemes have been proposed utilizing various types of detectors and decision strategies in different application areas. A common feature of all synchronization schemes is that the received signal and the locally generated signal are firstly correlated to produce a measure of similarity between the two. Secondly, this measure of similarity is compared to a threshold to decide if the two signals are in synchronism. If synchronization is detected, the tracking loop takes over. If there is no synchronization, the acquisition procedure provides a change in the phase of the locally generated PN code and another correlation is attempted as a part of a system search through the receiver's phase space.
There are two dwell time (or integration interval) schemes used for correlation, i.e., a fixed dwell time and a variable dwell time. The fixed dwell time approach is relatively simple to implement and analyze and, as a result, finds widespread use. The fixed dwell time technique can be implemented in one of two ways, i.e., as a single dwell time and as a multiple dwell time.
The speed and accuracy of acquisition are among, the major factors that limit the performance of CDMA receivers. Initial code acquisition is generally the most difficult operation to be performed in any spread spectrum system because of the system performance impairment factors such as a low signal to noise ratio (SNR), a doppler shift and a fading environment. Of primary interest here is a low SNR environment, so that consideration will be given to two known acquisition techniques, i.e., the maximum likelihood approach, such as described by M. K. SIMONS, J. K. OMURA, et al., in "Spread Spectrum Communications", Volume III, Rockville, Md., Computer Science Press, 1985, and the serial search approach, such as described by J. K. HOLMES and C. C. CHEN, in "Acquisition Time Performance of PN Spread-Spectrum Systems," IEEE Trans. on Commun., pp 778-783, August 1977, and by D. M. DiCARLO and C. L. WEBER, in "Statistical Performance of Single Dwell Serial Synchronization Systems," IEEE Trans. on Commun., pp 1382-1388, Aug. 1980.
The maximum likelihood approach is the most robust acquisition approach to dealing with noise. This technique with a single dwell time requires that the received PN code signal be correlated with all possible code positions of the local PN code replica. The correlations can be performed in parallel and the corresponding detector outputs all pertain to the identical observation of the received signal (plus noise). The correlations can also be done serially, which is preferred because of the reduced hardware complexity. The correct PN alignment is chosen by a comparator for a local PN code phase position which produces the maximum integrated signal energy output from the detector. The acquisition can be accomplished rapidly because all possible code offsets are examined simultaneously. However, for long PN codes with large processing gain, such as those required in a CDMA spread spectrum system, the complexity of the parallel implementation involved or the time to search the entire code space in a serial implementation before reaching a decision often render this approach unacceptable.
The serial search approach involves a search which is performed by linearly varying the time difference between PN modulation on the received incoming PN code and the locally generated PN code with a continuous decision process determining when synchronization is achieved. This approach is also referred to in the literature as a single dwell serial sliding acquisition system and is illustrated in FIG. 1. As seen in the Figure, the Received PN code signal is combined, by multiplying, with the locally generated PN code signal from a Local PN Generator and the resultant signal is integrated in an Integrator and input for threshold comparison to a Compare Threshhold unit. If the comparison is positive (YES), a Correct code phase decision signal is output. If the comparison is negative (NO), a feedback signal is generated and sent to the Local PN Generator to update the phase of the local PN code phase. Updating is carried on in this manner until a positive output results at the Compare Threshold unit.
Since this test for synchronization is based on the crossing of a threshold, when compared with the serial maximum likelihood acquisition system mentioned above, this scheme trades off shorter acquisition time against reduced accuracy in detection of synchronization. This is due to the fact that the conventional serial search algorithm uses a fixed threshold, which is set a priori, so that the detection of synchronization is an approximation and thus inexact. Clearly, the best acquisition performance of the serial search approach or system would be obtained by using the optimal threshold for that system at the actual time of operation. However, in a practical communication environment, the optimal threshold is a function of signal to noise ratio (SNR) which, in a mobile system, may be quite different from one time and place to another.
In such a practical communication environment, to achieve efficient operation of a direct sequence spread spectrum (DSSS) receiver an automatic level control for the decision threshold must be used. There are several articles published on algorithms for automatic control of the decision threshold, such, for example, as two by S. G. GLISIC, i.e., "Automatic Decision Threshold Level Control (ADTLC) in Direct Sequence Spectrum Systems Based on Matched Filtering", IEEE Trans. on Commun., Vol.-36, pp 519-528, Apr. 1988, and "Automatic Decision Threshold Level Control in Direct-Sequence Spread Spectrum Systems", IEEE Trans. on Commun., Vol.-39, No. 2, pp 187-192, Feb. 1991.
These and most of the disclosed automatic threshold control algorithms exploit the statistics of noise characteristics by employing two parallel signal energy detectors. The statistics of noise characteristics are obtained by despreading a received signal through applying two time displaced versions of the local PN code to the two parallel signal detectors, and choosing the smaller signal energy from the two outputs of the detectors. These automatic threshold control algorithms use the instantaneous noise characteristics or a filtered version of noise statistics to control their decision threshold, such as described by S. G. GLISIC in the above-noted IEEE February 1991 article, and by co-inventor. S. CHUNG and S. CZAJA, in the commonly-assigned, U.S. Pat. No. 5,440,597 entitled "Double Dwell Maximum Likelihood Acquisition Systems with Continuous Decision Making for CDMA and Direct Spread Spectrum Systems".